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Learn to build agentic workflows and AI agents using LangGraph with local LLMs in this 22-minute tutorial. Discover the fundamentals of LangGraph, a framework for creating complex AI workflows, and implement practical examples using the Qwen3 model running locally through Ollama. Start with setting up your development environment using Jupyter notebooks and Ollama, then progress through building your first agentic workflow that demonstrates how to chain multiple AI operations together. Transform your workflow into a fully functional AI agent capable of autonomous decision-making and task execution. Master the core concepts of state management, node creation, and edge definition within LangGraph while working entirely on your local machine without requiring external API calls. Gain hands-on experience with practical implementations that you can immediately apply to your own AI projects, complete with code examples and step-by-step guidance for both beginners and intermediate developers looking to expand their AI agent development skills.
